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Record W803914181 · doi:10.1163/15707563-00002467

Problem behaviour of black bears (Ursus americanus) in central Ontario: the effects of hunting and natural food availability

2015· article· en· W803914181 on OpenAlexaffabout
Josef Hamr, Jesse N. Popp, Dorthy L. Brown, Frank F. Mallory

Bibliographic record

VenueAnimal Biology · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsLaurentian UniversityCambrian College
Fundersnot available
KeywordsUrsusForageNatural (archaeology)GeographyEcologySpring (device)BiologyDemographyEngineering

Abstract

fetched live from OpenAlex

Problem bear behaviour in residential areas often results in human anxiety and potential injury, bear mortality and demographic instability. Identifying and understanding factors related to problem bear activity and encounters is important for developing successful management strategies. Indices of natural bear forage availability and hunting pressure were related to problem bear activity in central Ontario. Data were collected 5 years before and 5 years after the cancellation of a spring bear hunt, providing a unique opportunity to study the effect of management policy on problem behaviour. Problem bear activity indices increased significantly following the closure of the spring hunt. Natural food availability from the previous year was found to be highly correlated with early season problem bear activity indices; however, natural food availability during the same year was not significantly related to early or late season problem activity rates. This demonstrates that multiple potential causal agents of problem bear behaviour need to be considered when developing management strategies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.217
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2015
Admission routes2
Has abstractyes

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